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Empirical studies in software engineering use software repositories as data sources to understand software development. Repository data is either used to answer questions that guide the decision-making in the software development, or to provide tools that help with practical aspects of developers’ everyday work. Studies are classified into the field of Empirical Software Engineering (ESE), and more specifically into Mining Software Repositories (MSR). Studies working with repository data often focus on their results. Results are statements or tools, derived from the data, that help with practical aspects of software development. This thesis focuses on the methods and high order methods used to produce such results. In particular, we focus on incremental methods to scale the processing of repositories, declarative methods to compose a heterogeneous analysis, and high order methods used to reason about threats to methods operating on repositories. We summarize this as technical and methodological improvements. We contribute the improvements to methods and high-order methods in the context of MSR/ESE to produce future empirical results more effectively. We contribute the following improvements. We propose a method to improve the scalability of functions that abstract over repositories with high revision count in a theoretically founded way. We use insights on abstract algebra and program incrementalization to define a core interface of highorder functions that compute scalable static abstractions of a repository with many revisions. We evaluate the scalability of our method by benchmarks, comparing a prototype with available competitors in MSR/ESE. We propose a method to improve the definition of functions that abstract over a repository with a heterogeneous technology stack, by using concepts from declarative logic programming and combining them with ideas on megamodeling and linguistic architecture. We reproduce existing ideas on declarative logic programming with languages close to Datalog, coming from architecture recovery, source code querying, and static program analysis, and transfer them from the analysis of a homogeneous to a heterogeneous technology stack. We provide a prove-of-concept of such method in a case study. We propose a high-order method to improve the disambiguation of threats to methods used in MSR/ESE. We focus on a better disambiguation of threats, operationalizing reasoning about them, and making the implications to a valid data analysis methodology explicit, by using simulations. We encourage researchers to accomplish their work by implementing ‘fake’ simulations of their MSR/ESE scenarios, to operationalize relevant insights about alternative plausible results, negative results, potential threats and the used data analysis methodologies. We prove that such way of simulation based testing contributes to the disambiguation of threats in published MSR/ESE research.
Focusing on the triangulation of detective fiction, masculinity studies and disability studies, "Investigating the Disabled Detective – Disabled Masculinity and Masculine Disability in Contemporary Detective Fiction" shows that disability challenges common ideals of (hegemonic) masculinity as represented in detective fiction. After a theoretical introduction to the relevant focal points of the three research fields, the dissertation demonstrates that even the archetypal detectives Dupin and Holmes undermine certain nineteenth-century masculine ideals with their peculiarities. Shifting to contemporary detective fiction and adopting a literary disability studies perspective, the dissertation investigates how male detectives with a form of neurodiversity or a physical impairment negotiate their masculine identity in light of their disability in private and professional contexts. It argues that the occupation as a detective supports the disabled investigator to achieve ‘masculine disability’. Inversing the term ‘disabled masculinity’, predominantly used in research, ‘masculine disability’ introduces a decisively gendered reading of neurodiversity and (acquired) physical impairment in contemporary detective fiction. The term implies that the disabled detective (re)negotiates his masculine identity by implementing the disability in his professional investigations and accepting it as an important, yet not defining, characteristic of his (gender) identity. By applying this approach to five novels from contemporary British and American detective fiction, the dissertation demonstrates that masculinity and disability do not negate each other, as commonly assumed. Instead, it emphasises that disability allows the detective, as much as the reader, to rethink masculinity.
The biodegradable polymers polylactic acid (PLA) and polyhydroxybutyrate (PHB) produced from renewable raw materials were coated with hydrogenated amorphous carbon layers (a-C:H) at different deposition angles with various thicknesses as part of this thesis. Similar to conventional polymers, biopolymers often have unsuitable surface properties for industrial purposes, e.g. low hardness. For some applications, it is therefore necessary and advantageous to modify the surface properties of biopolymers while retaining the main properties of the substrate material. A suitable surface modification is the deposition of thin a-C:H layers. Their properties depend essentially on the sp² and sp³ hybridization ratio of the carbon atoms and the content of hydrogen atoms. The sp²/sp³ ratio was to be controlled in the present work by varying the coating geometry. Since coatings at 0°, directly in front of the plasma source, contain a higher percentage of sp³ and indirectly coated (180°) a higher amount of sp², it is shown in this work that it is possible to control the sp²/sp³ ratio. For this purpose, the samples are placed in front of the plasma source at angles of 0, 30, 60, 90, 120, 150 and 180° and coated for 2.5, 5.0, 7.5 and 10.0 minutes. For the angles 0°, the layer thicknesses were 25, 50, 75 and 100 nm. The a-C:H layers were all deposited using radio-frequency plasma-enhanced chemical vapor deposition and acetylene as C and H sources after being pretreated with an oxygen plasma for 10 minutes. Following the O₂ treatment and the a-C:H deposition, the surfaces are examined using macroscopic and microscopic measurement methods and the data is then analyzed. The surface morphology is recorded using scanning electron microscopy and atomic force microscopy. In addition, data on the stability of the layer and the surface roughness can be collected. Contact angle (CA) measurements are used to determine not only the wettability, but also the contact angle hysteresis by pumping the drop volume up and down. By measuring the CA with different liquids and comparing them, the surface free energy (SFE) and its polar and disperse components are determined. The changes in barrier properties are verified by water vapor transmission rate tests (WVTR). The chemical analysis of the surface is carried out on the one hand by Fourier transform infrared spectroscopy with specular reflection and on the other hand by synchrotron-supported techniques such as near-edge X-ray absorption fine structure and X-ray photoelectron spectroscopy. When analyzing the surfaces after the O₂ treatment, which was initially assumed to serve only to clean and activate the surface for the a-C:H coating, it was found that the changes were more drastic than originally assumed. For example, if PLA is treated at 0° for 10 minutes, the roughness increases fivefold. As the angle increases, it decreases again until it returns to the initial value at 180°. This can be recognized to a lesser extent with PHB at 30°. For both polymers, it can be shown that the polar fraction of the SFE increases. In the WVTR, a decrease in permeability can be observed for PLA and an increase in the initial value for PHB. The chemical surface analysis shows that the O₂ treatment has little effect on the surface bonds. Overall, it can be shown in this work that the O₂ treatment has an effect on the properties of the surface and cannot be regarded exclusively as a cleaning and activation process. With direct a-C:H coating (at 0°), a layer failure due to internal stress can be observed for both PLA and PHB. This also occurs with PHB at 30°, but to a lesser extent. Permeability of the polymers is reduced by 47% with a five-minute coating and the layer at 10.0 minutes continues to have this effect despite cracks appearing. The application of a-C:H layers shows a dominance of sp³ bonds for both polymer types with direct coating. This decreases with increasing angle and sp² bonds become dominant for indirect coatings. This result is similar for all coating thicknesses, only the angle at which the change of the dominant bond takes place is different. It is shown that it is possible to control the surface properties by an angle-dependent coating and thus to control the ratio sp²/sp³.
In international business relationships, such as international railway operations, large amounts of data can be exchanged among the parties involved. For the exchange of such data, a limited risk of being cheated by another party, e.g., by being provided with fake data, as well as reasonable cost and a foreseeable benefit, is expected. As the exchanged data can be used to make critical business decisions, there is a high incentive for one party to manipulate the data in its favor. To prevent this type of manipulation, mechanisms exist to ensure the integrity and authenticity of the data. In combination with a fair exchange protocol, it can be ensured that the integrity and authenticity of this data is maintained even when it is exchanged with another party. At the same time, such a protocol ensures that the exchange of data only takes place in conjunction with the agreed compensation, such as a payment, and that the payment is only made if the integrity and authenticity of the data is ensured as previously agreed. However, in order to be able to guarantee fairness, a fair exchange protocol must involve a trusted third party. To avoid fraud by a single centralized party acting as a trusted third party, current research proposes decentralizing the trusted third party, e.g., by using a distributed ledger based fair exchange protocol. However, for assessing the fairness of such an exchange, state-of-the-art approaches neglect costs arising for the parties conducting the fair exchange. This can result in a violation of the outlined expectation of reasonable cost, especially when distributed ledgers are involved, which are typically associated with non-negligible costs. Furthermore, the performance of typical distributed ledger-based fair exchange protocols is limited, posing an obstacle to widespread adoption.
To overcome the challenges, in this thesis, we introduce the foundation for a data exchange platform allowing for a fully decentralized fair data exchange with reasonable cost and performance. As a theoretical foundation, we introduce the concept of cost fairness, which considers cost for the fairness assessment by requesting that a party following the fair exchange protocol never suffers any unilateral disadvantages. We prove that cost fairness cannot be achieved using typical public distributed ledgers but requires customized distributed ledger instances, which usually lack complete decentralization. However, we show that the highest unilateral cost are caused by a grieving attack.
To allow fair data exchanges to be conducted with reasonable cost and performance, we introduce FairSCE, a distributed ledger-based fair exchange protocol using distributed ledger state channels and incorporating a mechanism to protect against grieving attacks, reducing the possible unilateral cost that have to be covered to a minimum. Based on our evaluation of FairSCE, the worst-case cost for data exchange, even in the presence of malicious parties, is known, which allows an estimate of the possible benefit and, thus, the preliminary estimate of economic utility. Furthermore, to allow for an unambiguous assessment of the correct data being transferred while still allowing for sensitive parts of the data to be masked, we introduce an approach for the hashing of hierarchically structured data, which can be used to ensure integrity and authenticity of the data being transferred.
How to begin? This short question addresses a problem that is anything but simple, especially when regarding something as sophisticated and multilayered as musical theatre. However, scholars of this vast research area have mostly neglected this question so far. This study analyses and compares the initial sections of late Victorian popular musical theatre and is therefore a contribution to several fields of research: the analysis of initial sections of musical theatre in general, the analysis of the music of popular musical theatre in particular, and therefore operetta studies. The 1890s are especially interesting times for popular musical theatre in London: The premiered works include the last collaborations of Gilbert and Sullivan as well as offshoots of Savoy opera; but the so-called ‘naughty nineties’ also saw the emergence of a new genre, musical comedy, which captured the late Victorian zeitgeist like no other. This new form of theatrical entertainment was carefully and consciously constructed and promoted as modern and fashionable, walking a fine line between respectability and mildly risqué excitement.
Because a deep understanding of the developments and new tendencies concerning popular musical theatre in the 1890s is crucial in order to interpret differences as well as similarities, the analyses of the opening numbers are preceded by a detailed discussion of the relevant genres: comic opera, musical comedy, musical play and operetta. Since the producers of the analysed works wanted to distance themselves from former and supposedly old-fashioned traditions, this book also considers influences from their British predecessors, but also from Viennese operetta and French opéra bouffe.
The goal of this PhD thesis is to investigate possibilities of using symbol elimination for solving problems over complex theories and analyze the applicability of such uniform approaches in different areas of application, such as verification, knowledge representation and graph theory. In the thesis we propose an approach to symbol elimination in complex theories that follows the general idea of combining hierarchical reasoning with symbol elimination in standard theories. We analyze how this general approach can be specialized and used in different areas of application.
In the verification of parametric systems it is important to prove that certain safety properties hold. This can be done by showing that a property is an inductive invariant of the system, i.e. it holds in the initial state of the system and is invariant under updates of the system. Sometimes this is not the case for the condition itself, but for a stronger condition it is. In this thesis we propose a method for goal-directed invariant strengthening.
In knowledge representation we often have to deal with huge ontologies. Combining two ontologies usually leads to new consequences, some of which may be false or undesired. We are interested in finding explanations for such unwanted consequences. For this we propose a method for computing interpolants in the description logics EL and EL⁺, based on a translation to the theory of semilattices with monotone operators and a certain form of interpolation in this theory.
In wireless network theory one often deals with classes of geometric graphs in which the existence or non-existence of an edge between two vertices in a graph relies on properties on their distances to other nodes. One possibility to prove properties of those graphs or to analyze relations between the graph classes is to prove or disprove that one graph class is contained in the other. In this thesis we propose a method for checking inclusions between geometric graph classes.
In the last decade, policy-makers around the world have turned their attention toward the creative industry as the economic engine and significant driver of employments. Yet, the literature suggests that creative workers are one of the most vulnerable work-forces of today’s economy. Because of the highly deregulated and highly individuated environment, failure or success are believed to be the byproduct of individual ability and commitment, rather than a structural or collective issue. This thesis taps into the temporal, spatial, and social resolution of digital behavioural data to show that there are indeed structural and historical issues that impact individuals’ and
groups’ careers. To this end, this thesis offers a computational social science research framework that brings together the decades-long theoretical and empirical knowledge of inequality studies, and computational methods that deal with the complexity and scale of digital data. By taking music industry and science as use cases, this thesis starts off by proposing a novel gender detection method that exploits image search and face-detection methods.
By analysing the collaboration patterns and citation networks of male and female computer scientists, it sheds lights on some of the historical biases and disadvantages that women face in their scientific career. In particular, the relation of scientific success and gender-specific collaboration patterns is assessed. To elaborate further on the temporal aspect of inequalities in scientific careers, this thesis compares the degree of vertical and horizontal inequalities among the cohorts of scientists that started their career at different point in time. Furthermore, the structural inequality in music industry is assessed by analyzing the social and cultural relations that breed from live performances and musics releases. The findings hint toward the importance of community belonging at different stages of artists’ careers. This thesis also quantifies some of the underlying mechanisms and processes of inequality, such as the Matthew Effect and the Hipster Paradox, in creative careers. Finally, this thesis argues that online platforms such as Wikipedia could reflect and amplify the existing biases.
The diversity within amphibian communities in cultivated areas in Rwanda and within two selected, taxonomically challenging groups, the genera Ptychadena and Hyperolius, were investigated in this thesis. The amphibian community of an agricultural wetland near Butare in southern Rwanda comprised 15 anuran species. Rarefaction and jackknife analyses corroborated that the complete current species richness of the assemblage had been recorded, and the results of acoustic niche analysis suggested species saturation of the community. Surveys at many other Rwandan localities showed that the species recorded in Butare are widespread in cultivated and pristine wetlands. The species were readily distinguishable using morphological, bioacoustic, and molecular (DNA barcoding) features, but only eight of the 15 species could be assigned unambiguously to nominal species. The remaining represented undescribed or currently unrecognized taxa, including three species of Hyperolius, two Phrynobatrachus species, one Ptychadena species, and one species of Amietia. The diversity of the Ridged Frogs in Rwanda was investigated in two studies (Chapters III and IV). Three species of Ptychadena were recorded in wetlands in the catchment of the Nile. They can be distinguished by morphological characters (morphometrics and qualitative features) as well as by their advertisement calls and genetics. The Rwandan species of the P. mascareniensis group was shown to differ from the topotypic population as well as from other genetic lineages in sub-Saharan Africa and an old available name, P. nilotica, was resurrected from synonymy for this lineage. Two further Ptychadena species were identified among voucher specimens from Rwanda deposited in the collection of the RMCA, P. chrysogaster and P. uzungwensis. Morphologically they can be unambiguously distinguished from each other and the three other Rwandan species. A key based on qualitative morphological characters was developed, which allows unequivocal identification of specimens of all species that have been recorded from Rwanda. DNA was isolated from a Rwandan voucher specimen of P. chrysogaster, and the genetic analysis corroborated the species" distinct status.
A species of Hyperolius collected in the Nyungwe National Park was compared to all other Rwandan species of the genus and to morphologically or genetically similar species from neighbouring countries. Its distinct taxonomic status was justified by morphological, bioacoustic, and molecular evidence and it was described as a new species, H. jackie. A species of the H. nasutus group collected at agricultural sites in Rwanda was described as a new species in the course of a revision of the species of the Hyperolius nasutus group. The group was shown to consist of 15 distinct species which can be distinguished from each other genetically, bioacoustically, and morphologically.
The aerial performance, i.e. parachuting, of the Disc-fingered Reed Frog, Hyperolius discodactylus, was described. It represents a novel observation of a behaviour that has been known from a number of Southeast Asian and Neotropical frog species. Parachuting frogs, including H. discodactylus, exhibit certain morphological characteristics and, while airborne, assume a distinct posture which is best-suited for maneuvering in the air. Another study on the species addressed the validity of the taxon H. alticola which had been considered either a synonym of H. discodactylus or a distinct species. Type material of both taxa was re-examined and the status of H. alticola reassessed using morphological data from historic and new collections, call recordings, and molecular data from animals collected on recent expeditions. A northern and a southern genetic clade were identified, a divide that is weakly supported by diverging morphology of the vouchers from the respective localities. No distinction in advertisement call features could be recovered to support this split and both genetic and morphological differences between the two geographic clades are marginal and not always congruent and more likely reflect population-level variation. Therefore it was concluded that H. alticola is not a valid taxon and should be treated as a synonym of H. discodactylus.
On the recognition of human activities and the evaluation of its imitation by robotic systems
(2023)
This thesis addresses the problem of action recognition through the analysis of human motion and the benchmarking of its imitation by robotic systems.
For our action recognition related approaches, we focus on presenting approaches that generalize well across different sensor modalities. We transform multivariate signal streams from various sensors to a common image representation. The action recognition problem on sequential multivariate signal streams can then be reduced to an image classification task for which we utilize recent advances in machine learning. We demonstrate the broad applicability of our approaches formulated as a supervised classification task for action recognition, a semi-supervised classification task for one-shot action recognition, modality fusion and temporal action segmentation.
For action classification, we use an EfficientNet Convolutional Neural Network (CNN) model to classify the image representations of various data modalities. Further, we present approaches for filtering and the fusion of various modalities on a representation level. We extend the approach to be applicable for semi-supervised classification and train a metric-learning model that encodes action similarity. During training, the encoder optimizes the distances in embedding space for self-, positive- and negative-pair similarities. The resulting encoder allows estimating action similarity by calculating distances in embedding space. At training time, no action classes from the test set are used.
Graph Convolutional Network (GCN) generalized the concept of CNNs to non-Euclidean data structures and showed great success for action recognition directly operating on spatio-temporal sequences like skeleton sequences. GCNs have recently shown state-of-the-art performance for skeleton-based action recognition but are currently widely neglected as the foundation for the fusion of various sensor modalities. We propose incorporating additional modalities, like inertial measurements or RGB features, into a skeleton-graph, by proposing fusion on two different dimensionality levels. On a channel dimension, modalities are fused by introducing additional node attributes. On a spatial dimension, additional nodes are incorporated into the skeleton-graph.
Transformer models showed excellent performance in the analysis of sequential data. We formulate the temporal action segmentation task as an object detection task and use a detection transformer model on our proposed motion image representations. Experiments for our action recognition related approaches are executed on large-scale publicly available datasets. Our approaches for action recognition for various modalities, action recognition by fusion of various modalities, and one-shot action recognition demonstrate state-of-the-art results on some datasets.
Finally, we present a hybrid imitation learning benchmark. The benchmark consists of a dataset, metrics, and a simulator integration. The dataset contains RGB-D image sequences of humans performing movements and executing manipulation tasks, as well as the corresponding ground truth. The RGB-D camera is calibrated against a motion-capturing system, and the resulting sequences serve as input for imitation learning approaches. The resulting policy is then executed in the simulated environment on different robots. We propose two metrics to assess the quality of the imitation. The trajectory metric gives insights into how close the execution was to the demonstration. The effect metric describes how close the final state was reached according to the demonstration. The Simitate benchmark can improve the comparability of imitation learning approaches.
With the increasing importance and urgency of climate change, companies are challenged to contribute to sustainable development, especially by younger generations. However, existing corporate contributions have been criticized as insufficient, which could be particularly caused by a lack of employee engagement in corporate sustainability. In this context, gamification has been proposed and increasingly investigated in recent years as a promising, innovative tool to motivate sustainable employee behaviors in the workplace. However, there are few studies and applicable gamification solutions that address more than one specific sustainability issue and thus take a holistic perspective on sustainable behaviors in the workplace. Moreover, previous research lacks a comprehensive understanding of how different gamification elements elicit specific psychological effects, how these manifest in behavioral changes, and how these, in turn, cumulatively result in measurable corporate outcomes. The path from gamification as ”input” to corporate sustainability as ”output” thus remains unexplored.
This dissertation fills this gap by conceptualizing, designing, and evaluating a holistic gamified intervention that supports employees in various sustainable behaviors in their daily activities. The project uses a design science research approach that closely involves employees in the incremental development of the solution. As part of the iterative design process, this dissertation presents six studies to extend the theoretical understanding of gamification for sustainable employee behaviors. First, a comprehensive review of existing research on gamification for sustainable employee behavior is provided, analyzing gamification designs and results of previous studies and outlining an agenda for further research (Study 1). Theoretical foundations of research on gamification, serious games, and game-based learning (Study 2) and empirical design principles for gamification and persuasive systems (Study 3) are then systematically reviewed as a basis for the successful design of gamified applications. Subsequently, empirical studies explore employees’ motivations for sustainable behavior and illuminate their expectations for design features (Study 4), and identify contextual challenges and design dilemmas when implementing gamification in an organizational context (Study 5). Finally, a quantitative field study (Study 6) explores how different gamification designs influence sustainable employee behavior and corporate sustainability in organizations. Based on the findings, this dissertation presents a comprehensive framework of gamification for sustainable employee behavior that incorporates design, individual behavior, and organizational perspectives. Finally, building on these insights, it provides practical recommendations for designing gamification to encourage sustainable employee behavior at work.
Leichte Sprache (LS, easy-to-read German) is a simplified variety of German. It is used to provide barrier-free texts for a broad spectrum of people, including lowliterate individuals with learning difficulties, intellectual or developmental disabilities (IDD) and/or complex communication needs (CCN). In general, LS authors are proficient in standard German and do not belong to the aforementioned group of people. Our goal is to empower the latter to participate in written discourse themselves. This requires a special writing system whose linguistic support and ergonomic software design meet the target group’s specific needs. We present EasyTalk a system profoundly based on natural language processing (NLP) for assistive writing in an extended variant of LS (ELS). EasyTalk provides users with a personal vocabulary underpinned with customizable communication symbols and supports in writing at their individual level of proficiency through interactive user guidance. The system minimizes the grammatical knowledge needed to produce correct and coherent complex contents by intuitively formulating linguistic decisions. It provides easy dialogs for selecting options from a natural-language paraphrase generator, which provides context-sensitive suggestions for sentence components and correctly inflected word forms. In addition, EasyTalk reminds users to add text elements that enhance text comprehensibility in terms of audience design (e.g., time and place of an event) and improve text coherence (e.g., explicit connectors to express discourse-relations). To tailor the system to the needs of the target group, the development of EasyTalk followed the principles of human-centered design (HCD). Accordingly, we matured the system in iterative development cycles, combined with purposeful evaluations of specific aspects conducted with expert groups from the fields of CCN, LS, and IT, as well as L2 learners of the German language. In a final case study, members of the target audience tested the system in free writing sessions. The study confirmed that adults with IDD and/or CCN who have low reading, writing, and computer skills can write their own personal texts in ELS using EasyTalk. The positive feedback from all tests inspires future long-term studies with EasyTalk and further development of this prototypical system, such as the implementation of a so-called Schreibwerkstatt (writing workshop)
In the last years, the public interest in epidemiology and mathematical modeling of disease spread has increased - mainly caused by the COVID-19 pandemic, which has emphasized the urgent need for accurate and timely modelling of disease transmission. However, even prior to that, mathematical modelling has been used for describing the dynamics and spread of infectious diseases, which is vital for developing effective interventions and controls, e.g., for vaccination campaigns and social restrictions like lockdowns. The forecasts and evaluations provided by these models influence political actions and shape the measures implemented to contain the virus.
This research contributes to the understanding and control of disease spread, specifically for Dengue fever and COVID-19, making use of mathematical models and various data analysis techniques. The mathematical foundations of epidemiological modelling, as well as several concepts for spatio-temporal diffusion like ordinary differential equation (ODE) models, are presented, as well as an originally human-vector model for Dengue fever, and the standard (SEIR)-model (with the potential inclusion of an equation for deceased persons), which are suited for the description of COVID-19. Additionally, multi-compartment models, fractional diffusion models, partial differential equations (PDE) models, and integro-differential models are used to describe spatial propagation of the diseases.
We will make use of different optimization techniques to adapt the models to medical data and estimate the relevant parameters or finding optimal control techniques for containing diseases using both Metropolis and Lagrangian methods. Reasonable estimates for the unknown parameters are found, especially in initial stages of pandemics, when little to no information is available and the majority of the population has not got in contact with the disease. The longer a disease is present, the more complex the modelling gets and more things (vaccination, different types, etc.) appear and reduce the estimation and prediction quality of the mathematical models.
While it is possible to create highly complex models with numerous equations and parameters, such an approach presents several challenges, including difficulties in comparing and evaluating data, increased risk of overfitting, and reduced generalizability. Therefore, we will also consider criteria for model selection based on fit and complexity as well as the sensitivity of the model with respect to specific parameters. This also gives valuable information on which political interventions should be more emphasized for possible variations of parameter values.
Furthermore, the presented models, particularly the optimization using the Metropolis algorithm for parameter estimation, are compared with other established methods. The quality of model calculation, as well as computational effort and applicability, play a role in this comparison. Additionally, the spatial integro-differential model is compared with an established agent-based model. Since the macroscopic results align very well, the computationally faster integro-differential model can now be used as a proxy for the slower and non-traditionally optimizable agent-based model, e.g., in order to find an apt control strategy.
In a world where language defines the boundaries of one's understanding, the words of Austrian philosopher Ludwig Wittgenstein resonate profoundly. Wittgenstein's assertion that "Die Grenzen meine Sprache bedeuten die Grenzen meiner Welt" (Wittgenstein 2016: v. 5.6) underscores the vital role of language in shaping our perceptions. Today, in a globalized and interconnected society, fluency in foreign languages is indispensable for individual success. Education must break down these linguistic barriers, and one promising approach is the integration of foreign languages into content subjects.
Teaching content subjects in a foreign language, a practice known as Content Language Integrated Learning (CLIL), not only enhances language skills but also cultivates cognitive abilities and intercultural competence. This approach expands horizons and aligns with the core principles of European education (Leaton Gray, Scott & Mehisto 2018: 50). The Kultusministerkonferenz (KMK) recognizes the benefits of CLIL and encourages its implementation in German schools (cf. KMK 2013a).
With the rising popularity of CLIL, textbooks in foreign languages have become widely available, simplifying teaching. However, the appropriateness of the language used in these materials remains an unanswered question. If textbooks impose excessive linguistic demands, they may inadvertently limit students' development and contradict the goal of CLIL.
This thesis focuses on addressing this issue by systematically analyzing language requirements in CLIL teaching materials, emphasizing receptive and productive skills in various subjects based on the Common European Framework of Reference. The aim is to identify a sequence of subjects that facilitates students' language skill development throughout their school years. Such a sequence would enable teachers to harness the full potential of CLIL, fostering a bidirectional approach where content subjects facilitate language learning.
While research on CLIL is extensive, studies on language requirements for bilingual students are limited. This thesis seeks to bridge this gap by presenting findings for History, Geography, Biology, and Mathematics, allowing for a comprehensive understanding of language demands. This research endeavors to enrich the field of bilingual education and CLIL, ultimately benefiting the academic success of students in an interconnected world.
The trends of industry 4.0 and the further enhancements toward an ever changing factory lead to more mobility and flexibility on the factory floor. With that higher need of mobility and flexibility the requirements on wireless communication rise. A key requirement in that setting is the demand for wireless Ultra-Reliability and Low Latency Communication (URLLC). Example use cases therefore are cooperative Automated Guided Vehicles (AGVs) and mobile robotics in general. Working along that setting this thesis provides insights regarding the whole network stack. Thereby, the focus is always on industrial applications. Starting on the physical layer, extensive measurements from 2 GHz to 6 GHz on the factory floor are performed. The raw data is published and analyzed. Based on that data an improved Saleh-Valenzuela (SV) model is provided. As ad-hoc networks are highly depended onnode mobility, the mobility of AGVs is modeled. Additionally, Nodal Encounter Patterns (NEPs) are recorded and analyzed. A method to record NEP is illustrated. The performance by means of latency and reliability are key parameters from an application perspective. Thus, measurements of those two parameters in factory environments are performed using Wireless Local Area Network (WLAN) (IEEE 802.11n), private Long Term Evolution (pLTE) and 5G. This showed auto-correlated latency values. Hence, a method to construct confidence intervals based on auto-correlated data containing rare events is developed. Subsequently, four performance improvements for wireless networks on the factory floor are proposed. Of those optimization three cover ad-hoc networks, two deal with safety relevant communication, one orchestrates the usage of two orthogonal networks and lastly one optimizes the usage of information within cellular networks.
Finally, this thesis is concluded by an outlook toward open research questions. This includes open questions remaining in the context of industry 4.0 and further the ones around 6G. Along the research topics of 6G the two most relevant topics concern the ideas of a network of networks and overcoming best-effort IP.
Harvesting Season?
(2022)
Efforts to induce customers to buy groceries through the Internet have existed for around twenty years. Early on, the market structures of the digital grocery trade were still strongly fragmented and poorly coordinated. Due to the technological advancement in the past decade, the digital purchase of groceries has become more attractive. The adoption rate of these services varies greatly between different regions. In Germany in particular, the digital grocery trade is stagnating at a comparatively low level. In this regard, this dissertation analyzes both the retail-side market structures and the expectations and obstacles of German consumers.
The year 2020 connotes a turning point for the online grocery trade, as daily routines such as grocery shopping were subject to strict regulations imparted at a governmental level in order to reduce COVID-19 infections. At the same time, despite this opportunity, the digital grocery trade has not yet established itself nationwide in Germany. This can be attributed to a lack of investments, but also to inadequate digitization measures. A stronger synchronization between the digital and stationary offer, better integration of digital food services at a regional level as well as adapted, target group-appropriate digital solutions for the efficient breakdown of usage barriers will benefit service usage. The importance of stable food chains and distribution channels was illustrated by the COVID-19 pandemic. Further research should help to develop the digital food trade into a stable and sustainable supplementation of the stationary store.
Today’s agriculture heavily relies on pesticides to manage diverse pests and maximise crop yields. Despite elaborate regulation of pesticide use based on a complex environmental risk assessment (ERA) scheme, the widespread use of these biologically active compounds has been shown to be a threat to the environment. For surface waters, pesticide exposure has been observed to exceed safe concentration levels and negatively impact stream ecology leading to the question whether current ERA schemes ensure a sustainable use of pesticides. To answer this, the large-scale “Kleingewässer-Monitoring” (KgM) assessed the occurrence of pesticides and related effects in 124 streams throughout Germany, Central Europe, in 2018 and 2019.
Based on five scientific publications originating from the KgM, this thesis evaluated pesticide exposure in streams, ecological effects and the regulatory implications. More than 1,000 water samples were analysed for over 100 pesticide analytes to characterise occurrence patterns (publication 1). Measured concentrations and effects were used to validate the exposure and effect concentrations predicted in the ERA (publication 2). By jointly analysing real-world pesticide application data and measured pesticide mixtures in streams, the disregard of environmental pesticide mixtures in the ERA was evaluated (publication 3). The toxic potential of mixtures in stream water was additionally investigated using suspect screening for 395 chemicals and a battery of in-vitro bioassays (publication 4). Finally, the results from the KgM stream monitoring were used to assess the capability to identify pesticide risks in governmental monitoring programmes (publication 5).
The results of this thesis reveal the widespread occurrence of pesticides in non-target stream ecosystems. The water samples contained a variety of pesticides occurring in complex mixtures predominantly in short-term peaks after rainfall events (publications 1 & 4). Respective pesticide concentration maxima were linked to declines in vulnerable invertebrate species and exceeded regulatory acceptable concentrations in about 80% of agricultural streams, while these thresholds were still estimated partly insufficient to protect the invertebrate community (publication 2). The co-occurrence of pesticides in streams led to a risk underestimated in the single substance-oriented ERA by a factor of about 3.2 in realistic worst-case scenarios, which is further exacerbated by a high frequency at which non-target organism are exposed to pesticides (publication 3). Stream water samples taken after rainfall caused distinct effects in bioassays which were only explainable to a minor extent by the many analytes, indicating the relevance of unknown chemical or biological mixture components (publication 4). Finally, the regulatory monitoring of surface waters under the Water Framework Directive (WFD) was found to significantly underestimate pesticide risks, as about three quarters of critical pesticides and more than half of streams at risk were overlooked (publication 5).
Essentially, this thesis involves a new level of validation of the ERA of pesticides in aquatic ecosystems by assessing pesticide occurrence and environmental impacts at a scale so far unique. The overall results demonstrate that the current agricultural use of pesticides leads to significant impacts on stream ecology that go beyond the level tolerated under the ERA. This thesis identified the underestimation of pesticide exposure, the potential insufficiency of regulatory thresholds and the general inertia of the authorisation process as the main causes why the ERA fails to meet its objectives. To achieve a sustainable use of pesticides, the thesis proposes substantial refinements of the ERA. Adequate monitoring programmes such as the KgM, which go beyond current government monitoring efforts, will continue to be needed to keep pesticide regulators constantly informed of the validity of their prospective ERA, which will always be subject to uncertainty.
In the last decades, it became evident that the world is facing an unprecedented, human-induced global biodiversity crisis with amphibians being one of the most threatened species groups. About 41% of the amphibian species are classified as endangered by the IUCN, but even in amphibian species that are listed as "least concern", population declines can be observed on a local level. With land-use change and agrochemicals (i.e. pesticides), two of the main drivers for this amphibian decline are directly linked to intensive agriculture, which is the dominant landscape type in large parts of Europe. Thus, understanding the situation of amphibians in the agricultural landscape is crucial for conservation measures. In the present thesis, I investigated the effects of viticulture on amphibian populations around Landau in der Pfalz (Germany) in terms of habitat use, pesticide exposure, biometric traits as well as genetic and age structure. From the perspective of amphibians, land-use change means usually the destruction of habitats in agricultural landscapes, which often leads to landscape fragmentation. Thus, I followed the question if also vineyards lead to the fragmentation of the landscape and if pesticides that are frequently used in viticulture have to be considered as a factor too, so if there is a chemical landscape fragmentation. Using telemetry, I could show that common toads (Bufo bufo) can be found directly in vineyards, but that they tend to avoid them as habitat. Analysing the genetic structure of common frogs (Rana temporaria) revealed that vineyards have to be considered as a barrier for amphibians. To identify if pesticides contribute to the resulting landscape fragmentation, I conducted an arena choice experiment in the laboratory in which I found evidence for an avoidance of pesticide-contaminated soil. Such an avoidance could be one of the underlying reasons for a potential chemical landscape fragmentation. By combining telemetry data with information about pesticide applications from local wine growers, I could show that a large part of the common toads is likely to come in contact with pesticides. Further, I demonstrated that the agricultural landscape, probably due to the application of pesticides, can have negative effects on the reproduction capacity of common toads. By studying palmate newts (Lissotriton helveticus) I found that adult newts from agricultural ponds are smaller than those from forest ponds. As I did not find differences in the age structure and growth, these differences might be carry-over effects from earlier life stages. While agricultural ponds might be suitable habitats for adult palmate newts, the potential carry-over effect indicates suboptimal conditions for larvae and/or juveniles. I conclude that the best management measure for sustaining amphibians in the agricultural landscape would be a heterogeneous cultural landscape with a mosaic of different habitat patches that work without or at least a reduced amount of pesticides. Green corridors between populations and different habitats would allow migrating individuals to avoid agricultural and thus pesticide-contaminated areas. This would reduce the pesticide exposure risk of amphibians, while preventing the fragmentation of the landscape and thus the isolation of populations.
This thesis was motivated by the need to advance the knowledge on the variability and dynamics of energy fluxes in lakes and reservoirs, as well as about the physical processes that regulate the fluxes at both the air and water side of the air-water interface.
In the first part, I re-examine how mechanical energy, resulting from its major source – the vertical wind energy flux - distributes into the various types of water motions, including turbulent flows and surface and internal waves. Although only a small fraction of the wind energy flux from the atmosphere is transferred to the water, it is crucial for physical, biogeochemical and ecological processes in lentic ecosystems. Based on extensive air- and water-side measurements collected at two small water bodies (< 10 km2), we estimated the energy fluxes and energy content in surface and in internal waves. Overall, the estimated energy fluxes and energy content agree well with results reported for larger water bodies, suggesting that the energetics driving the water motions in enclosed basins is similar, independently of the basin size. Our findings highlight the importance of the surface waves that receive the largest fraction of the wind energy flux, which strongly nonlinearly increases for wind speeds exceeding 3 m s-1. We found that the existing parameterization of the wave height as a function of wind speed and fetch length did not reproduce the measured wave amplitude in lakes. On average, the highest energy content was observed in basin-scale internal waves, together with high-frequency internal waves exhibiting seasonal variability and varies among the aquatic systems. During our analysis, we discovered the diurnal variability of the energy dissipation rates in the studied lake, suggesting biogenic turbulence generation, which appears to be a widespread phenomenon in lakes and reservoirs.
In the second part of the thesis, I addressed current knowledge gaps related to the bulk transfer coefficients (also known as the drag coefficient, the Stanton number and the Dalton number), which are of a particular importance for the bulk estimation of the surface turbulent fluxes of momentum, sensible and latent heat in the atmospheric boundary layer. Their inaccurate representation may lead to significant errors in flux estimates, affecting, for example, the weather and climate predictions or estimations of the near-surface current velocities in lake hydrodynamic models. Although the bulk transfer coefficients have been extensively studied over the past several decades (mainly in marine and large-lake environments), there has been no systematic analysis of measurements obtained at lakes of different size. A significant increase of the transfer coefficients at low wind speeds (< 3 m s-1) has been observed in several studies, but, to date, it has remained unexplained. We evaluated
the bulk transfer coefficients using flux measurements from 31 lakes and reservoirs. The estimates were generally within the range reported in previous studies for large lakes and oceans. All transfer coefficients increased substantially at low wind speeds, which was found to be associated with the presence of gusts and capillary waves (except the Dalton number). We found that the Stanton number is systematically higher than the Dalton number. This challenges the assumption made in the Bowen-ratio method, which is widely used for estimating evaporation rates from micrometeorological measurements. We found that the variability of the transfer coefficients among the lakes could be associated with lake surface area. In flux parameterizations at lake surfaces, it is recommended to consider variations in the drag coefficient and the Stanton number due to wind gustiness and capillary wave roughness while the Dalton number could be considered as constant at all wind speeds.
In the third part of the thesis, I address the key drivers of the near-surface turbulence that control the gas exchange in a large regulated river. As all inland waters, rivers are an important natural source of greenhouse gases. The effects of the widespread alteration and regulation of river flow for human demands on gas exchange is largely unknown. In particular, the near-surface turbulence in regulated rivers has been rarely measured and its drivers have not been identified. While in lakes and reservoirs, near-surface turbulence is mainly related to atmospheric forcing, in shallow rivers and streams it is generated by bottom friction of the gravity-forced flow. The studied large regulated river represents a transition between these two cases. Atmospheric forcing and gravity were the dominant drivers of the near-surface turbulence for a similar fraction of the measurement period. Based on validated scalings, we derived a simple model for estimating the relative contributions of wind and bottom friction to near-surface turbulence in lotic ecosystems with different flow depths. Large diel variability in the near-surface energy dissipation rates due to flow regulation leads to the same variability in gas exchange. This suggests that estimates of gas fluxes from rivers are biased by measurements performed predominantly during daytime.
In addition, the novelty in all the analyses described above is the use of the turbulent surface fluxes measured directly by the eddy-covariance technique – at the moment of writing, the most advanced method. Overall, this thesis is of a potential interest for a broad range of scientific disciplines, including limnology, micrometeorology and open channel hydraulics.
This dissertation is dedicated to a new concept for capturing renunciation-oriented attitudes and beliefs — sufficiency orientation. Sufficiency originates in the interdisciplinary sustain-ability debate. In contrast to efficiency and consistency, sufficiency considers human behaviour as the cause of socio-ecological crises and strives for a reduction in consumption respecting the planetary boundaries. The present work places sufficiency in a psychological research context and explores it qualitatively and quantitatively. On the basis of five manuscripts, the overarching question pursued is to what extent sufficiency orientation contributes to socio-ecological transformation. Based on one qualitative study and five further quantitative studies, sufficiency orientation is investigated in different behavioural contexts that are of particular importance with regard to CO2 emissions. In addition, sufficiency orientation is linked to a wider range of psychologically relevant theories that help gain an overview of correlates and possible causes for the development of a sufficiency orientation.
Manuscript 1 uses expert interviews (N = 21) to develop a heuristic framework on a transformation towards societal sufficiency orientation including barriers and enablers, as well as ambiguities on such a change. The derived elements are interpreted in the light of the leverage points approach. This framework can serve as a heuristic for future research and to develop measures concerning sufficiency orientation.
As part of an online study (N = 648), Manuscript 2 examines the extent to which sufficiency orientation can be embedded in classic models for explaining pro-environmental intentions and behaviour (Theory of Planned Behaviour, Norm Activation Model), and showed a significant contribution to the explanation of intentions and behaviour in the field of plastic consumption.
Manuscript 3 reports two framing experiments (Study 1, N = 123, Study 2, N = 330) to investigate how pro-social justice sensitivity contributes to making sufficiency orientation more salient and promoting it. While sufficiency orientation and pro-social facets of justice sensitivity were positively related to each other, there was no effect of the framing intervention in the hypothesised direction. The results indicate that justice-related information at least in the presented manner is more likely to generate reactance.
Manuscript 4 presents an online study (N = 317) and targets the importance of sufficiency orientation for predicting actual greenhouse gas emissions in relation to flight behav-iour and policy support for the decarbonisation of mobility. In addition, the connection between sufficiency orientation and global identity is examined. It turns out that sufficiency orientation is superior to global identity in predicting actual emissions and decarbonisation policies. Contrary to expectations, sufficiency orientation and the form of global identity operationalised in the presented study shows a positive correlation and are compatible.
Manuscript 5 reports a reflective diary intervention (N = 252) that should lead to a short- and long-term increase in sufficiency orientation by satisfying basic psychological needs through induced self-reflection. For both groups with or without the intervention, sufficiency orientation increased slightly but significantly. Although no specific effect of the manipulation was found, basic psychological need satisfaction turns out to be the largest predictor for sufficiency orientation. Subjective well-being is positively associated with sufficiency orientation, while time affluence shows no clear associations in the study.
Overall, the results highlight the relevance of sufficiency orientation in relation to socio-ecological transformation and actual behavioural change. Sufficiency orientation is related to low-emission behaviour and support for political measures to decarbonize infrastructures. These results contribute to the discussion on the intention-behaviour gap in regard to impact-relevant behaviour, i.e. behaviour producing high emissions. The present findings suggest, that sufficiency orientation could be related to a strong intention-behavioural consistency. However, further research is needed to validate these results and improve the measurement of sufficiency orientation. Furthermore, the studies provided insights on correlates of sufficiency orientation: justice sensitivity, global identity, subjective well-being and left-wing liberal political ideologies are all found to be positively related to sufficiency orien-tation. Moreover, basic psychological need satisfaction was identified as a potential mechanism that can support the emergence of sufficiency orientation, however, causality remains unclear. From these findings, the work derives practical implications how to possibly strengthen sufficiency orientation on the micro, meso and macro levels of society.
Taken together, the dissertation provides important insights into a new and still developing concept, and shows its connectivity to psychological theories. However, future research is required in order to grasp more precisely the complexity of sufficiency orientation and to understand origins and predictors of sufficiency orientation. This work contributes to the interdisciplinary debate on socio-ecological transformation and points out that sufficiency orientation can serve to a future worth living as being related to reduced consumption.
Social networks are ubiquitous structures that we generate and enrich every-day while connecting with people through social media platforms, emails, and any other type of interaction. While these structures are intangible to us, they carry important information. For instance, the political leaning of our friends can be a proxy to identify our own political preferences. Similarly, the credit score of our friends can be decisive in the approval or rejection of our own loans. This explanatory power is being leveraged in public policy, business decision-making and scientific research because it helps machine learning techniques to make accurate predictions. However, these generalizations often benefit the majority of people who shape the general structure of the network, and put in disadvantage under-represented groups by limiting their resources and opportunities. Therefore it is crucial to first understand how social networks form to then verify to what extent their mechanisms of edge formation contribute to reinforce social inequalities in machine learning algorithms.
To this end, in the first part of this thesis, I propose HopRank and Janus two methods to characterize the mechanisms of edge formation in real-world undirected social networks. HopRank is a model of information foraging on networks. Its key component is a biased random walker based on transition probabilities between k-hop neighborhoods. Janus is a Bayesian framework that allows to identify and rank plausible hypotheses of edge formation in cases where nodes possess additional information. In the second part of this thesis, I investigate the implications of these mechanisms - that explain edge formation in social networks - on machine learning. Specifically, I study the influence of homophily, preferential attachment, edge density, fraction of inorities, and the directionality of links on both performance and bias of collective classification, and on the visibility of minorities in top-k ranks. My findings demonstrate a strong correlation between network structure and machine learning outcomes. This suggests that systematic discrimination against certain people can be: (i) anticipated by the type of network, and (ii) mitigated by connecting strategically in the network.